InĀ [1]:
linkWorldMap="https://github.com/CienciaDeDatosEspacial/intro_geodataframe/raw/main/maps/worldMaps.gpkg"


import geopandas as gpd
from  fiona import listlayers
listlayers(linkWorldMap)
Out[1]:
['countries', 'rivers', 'cities', 'indicators']
InĀ [2]:
countries=gpd.read_file(linkWorldMap,layer='countries')
rivers=gpd.read_file(linkWorldMap,layer='rivers')
cities=gpd.read_file(linkWorldMap,layer='cities')
indicators=gpd.read_file(linkWorldMap,layer='indicators')
InĀ [3]:
#Exercise 1
InĀ [4]:
countries.cx[:0,:0]
Out[4]:
COUNTRY geometry
9 American Samoa (US) POLYGON ((-170.74390 -14.37556, -170.74942 -14...
10 Argentina MULTIPOLYGON (((-71.01648 -36.47591, -70.98195...
14 Antarctica MULTIPOLYGON (((-45.14528 -60.76611, -45.15639...
24 Bolivia POLYGON ((-62.19884 -20.47139, -62.26945 -20.5...
29 Brazil MULTIPOLYGON (((-70.62862 -9.94849, -70.62889 ...
42 Chile MULTIPOLYGON (((-73.61806 -51.63390, -73.60494...
47 Colombia MULTIPOLYGON (((-81.71306 12.49028, -81.72014 ...
53 Cook Islands (New Zealand) MULTIPOLYGON (((-165.84167 -10.89084, -165.848...
58 Jarvis Island (US) POLYGON ((-160.02115 -0.39806, -160.02811 -0.3...
60 Ecuador MULTIPOLYGON (((-78.70903 -4.58479, -78.72348 ...
71 Fiji MULTIPOLYGON (((180.00000 -16.17274, 179.98621...
72 Falkland Islands (UK) MULTIPOLYGON (((-59.79139 -51.24945, -59.73195...
75 French Polynesia (France) MULTIPOLYGON (((-140.17783 -8.95639, -140.1894...
158 Niue (New Zealand) POLYGON ((-169.89389 -19.14556, -169.93088 -19...
169 New Zealand MULTIPOLYGON (((177.91779 -38.94280, 177.90970...
170 Paraguay POLYGON ((-57.67267 -25.29430, -57.70639 -25.2...
171 Pitcairn Islands (UK) MULTIPOLYGON (((-128.33221 -24.32727, -128.326...
172 Peru POLYGON ((-69.56750 -10.95056, -69.56844 -10.9...
196 St. Helena (UK) POLYGON ((-5.71298 -15.99286, -5.72917 -16.005...
208 South Georgia and the South Sandwich Is (UK) MULTIPOLYGON (((-36.99139 -54.35056, -36.99973...
216 Tokelau (New Zealand) POLYGON ((-171.84805 -9.21889, -171.85886 -9.2...
217 Tonga MULTIPOLYGON (((-173.93921 -18.56889, -173.933...
231 Uruguay POLYGON ((-58.38889 -33.42250, -58.41590 -33.4...
239 Wallis and Futuna (France) MULTIPOLYGON (((-176.16504 -13.35305, -176.169...
242 Western Samoa MULTIPOLYGON (((-172.59650 -13.50911, -172.551...
InĀ [5]:
argentina=countries[countries.COUNTRY=='Argentina']
InĀ [6]:
citiesArgentina_clipped = gpd.clip(gdf=cities,
                          mask=argentina)
riversArgentina_clipped = gpd.clip(gdf=rivers,
                               mask=argentina)
InĀ [7]:
base = argentina.plot(facecolor="lightblue", edgecolor='black', linewidth=0.4,figsize=(5,5))
No description has been provided for this image
InĀ [8]:
base = argentina.plot(facecolor="lightblue", edgecolor='black', linewidth=0.4,figsize=(5,5))
citiesArgentina_clipped.plot(marker='+', color='red', markersize=15,
                    ax=base)
Out[8]:
<Axes: >
No description has been provided for this image
InĀ [9]:
base = argentina.plot(facecolor="lightblue", edgecolor='black', linewidth=0.4,figsize=(5,5))
riversArgentina_clipped.plot(edgecolor='blue', linewidth=0.5,
                    ax=base)
Out[9]:
<Axes: >
No description has been provided for this image
InĀ [10]:
#Exercise 2
InĀ [11]:
argentina.to_crs(9252).crs.axis_info
Out[11]:
[Axis(name=Northing, abbrev=X, direction=north, unit_auth_code=EPSG, unit_code=9001, unit_name=metre),
 Axis(name=Easting, abbrev=Y, direction=east, unit_auth_code=EPSG, unit_code=9001, unit_name=metre)]
InĀ [12]:
argentina.to_crs(9252).centroid
Out[12]:
10    POINT (2890124.088 6156396.222)
dtype: geometry
InĀ [13]:
base9252=argentina.to_crs(9252).plot()
argentina.to_crs(9252).centroid.plot(color='red',ax=base9252)
Out[13]:
<Axes: >
No description has been provided for this image
InĀ [14]:
argentina_9252=argentina.to_crs(9252)
cities_argentina_9252=citiesArgentina_clipped.to_crs(argentina_9252.crs)
rivers_argentina_9252=riversArgentina_clipped.to_crs(argentina_9252.crs)
InĀ [15]:
base9252=argentina.to_crs(9252).plot()
rivers_argentina_9252.plot(edgecolor='black', linewidth=0.5,ax=base9252)
Out[15]:
<Axes: >
No description has been provided for this image
InĀ [16]:
base9252=argentina.to_crs(9252).plot()
cities_argentina_9252.plot(marker='+', color='red', markersize=15,ax=base9252)
Out[16]:
<Axes: >
No description has been provided for this image
InĀ [17]:
import os

ruta_actual = os.getcwd()
os.mkdir(os.path.join(ruta_actual, "maps"))
print("Carpeta 'maps' creada en la ruta:", ruta_actual)

Carpeta 'maps' creada en la ruta: C:\Users\ASUS
InĀ [18]:
argentina_9252.to_file(os.path.join("maps","argentinaMaps_9252.gpkg"), layer='country', driver="GPKG")
cities_argentina_9252.to_file(os.path.join("maps","argentinaMaps_9252.gpkg"), layer='cities', driver="GPKG")
rivers_argentina_9252.to_file(os.path.join("maps","argentinaMaps_9252.gpkg"), layer='rivers', driver="GPKG")
argentina_9252.centroid.to_file(os.path.join("maps","argentinaMaps_9252.gpkg"), layer='centroid', driver="GPKG")
InĀ [19]:
#Exercise 3
InĀ [20]:
import pandas as pd
infoairports=pd.read_csv('https://github.com/Luis9193/geodf_operations/raw/main/data/ar-airports.csv')

# some rows
infoairports.iloc[[0,1,2,3,-4,-3,-2,-1],:] #head and tail
Out[20]:
id ident type name latitude_deg longitude_deg elevation_ft continent country_name iso_country ... municipality scheduled_service gps_code iata_code local_code home_link wikipedia_link keywords score last_updated
0 #meta +id #meta +code #loc +airport +type #loc +airport +name #geo +lat #geo +lon #geo +elevation +ft #region +continent +code #country +name #country +code +iso2 ... #loc +municipality +name #status +scheduled #loc +airport +code +gps #loc +airport +code +iata #loc +airport +code +local #meta +url +airport #meta +url +wikipedia #meta +keywords #meta +score #date +updated
1 5781 SAEZ large_airport Minister Pistarini International Airport -34.8222 -58.5358 67 SA Argentina AR ... Buenos Aires (Ezeiza) 1 SAEZ EZE EZE http://www.aa2000.com.ar/index.php https://en.wikipedia.org/wiki/Ministro_Pistari... BUE, Ezeiza 1275 2022-10-27T15:05:29+00:00
2 5771 SABE large_airport Jorge Newbery Airpark -34.5592 -58.4156 18 SA Argentina AR ... Buenos Aires 1 SABE AEP AER NaN https://en.wikipedia.org/wiki/Aeroparque_Jorge... NaN 1050 2021-10-07T15:55:36+00:00
3 5835 SAWH medium_airport Malvinas Argentinas Airport -54.8433 -68.2958 102 SA Argentina AR ... Ushuaia 1 SAWH USH USU NaN https://en.wikipedia.org/wiki/Ushuaia_Internat... NaN 750 2021-10-07T11:21:29+00:00
940 42893 AR-0471 heliport Dayry Partners Americas Manufacturing Argentin... -32.44 -63.2289 639 SA Argentina AR ... Villa Nueva 0 NaN NaN HNE NaN NaN NaN 0 2009-10-20T11:13:21+00:00
941 333815 AR-0652 closed Villa UniĆ³n Airport -29.42218 -62.789526 248 SA Argentina AR ... Villa UniĆ³n 0 NaN NaN NaN NaN NaN NaN 0 2020-04-10T04:01:54+00:00
942 42903 AR-0481 heliport Roca Heliport -32.06 -64.7794 3444 SA Argentina AR ... Yacanto de Calamuchita 0 NaN NaN HYC NaN NaN NaN 0 2009-10-20T11:13:21+00:00
943 42905 AR-0483 heliport Austral S.A. Heliport -52.7386 -68.5725 290 SA Argentina AR ... Yacimiento CaƱadĆ³n Alfa 0 NaN NaN HCP NaN NaN NaN 0 2021-10-07T11:46:03+00:00

8 rows Ɨ 23 columns

InĀ [21]:
#eliminacion de filas
infoairports.drop(index=0,inplace=True)
infoairports.reset_index(drop=True, inplace=True)
infoairports.head()
Out[21]:
id ident type name latitude_deg longitude_deg elevation_ft continent country_name iso_country ... municipality scheduled_service gps_code iata_code local_code home_link wikipedia_link keywords score last_updated
0 5781 SAEZ large_airport Minister Pistarini International Airport -34.8222 -58.5358 67 SA Argentina AR ... Buenos Aires (Ezeiza) 1 SAEZ EZE EZE http://www.aa2000.com.ar/index.php https://en.wikipedia.org/wiki/Ministro_Pistari... BUE, Ezeiza 1275 2022-10-27T15:05:29+00:00
1 5771 SABE large_airport Jorge Newbery Airpark -34.5592 -58.4156 18 SA Argentina AR ... Buenos Aires 1 SABE AEP AER NaN https://en.wikipedia.org/wiki/Aeroparque_Jorge... NaN 1050 2021-10-07T15:55:36+00:00
2 5835 SAWH medium_airport Malvinas Argentinas Airport -54.8433 -68.2958 102 SA Argentina AR ... Ushuaia 1 SAWH USH USU NaN https://en.wikipedia.org/wiki/Ushuaia_Internat... NaN 750 2021-10-07T11:21:29+00:00
3 5831 SAWC medium_airport El Calafate - Commander Armando Tola Internati... -50.2803 -72.053101 669 SA Argentina AR ... El Calafate 1 SAWC FTE ECA http://www.aeropuertoelcalafate.com/en/ https://en.wikipedia.org/wiki/Comandante_Arman... NaN 500 2022-01-12T18:23:15+00:00
4 5806 SARI medium_airport Cataratas Del IguazĆŗ International Airport -25.737301 -54.4734 916 SA Argentina AR ... Puerto Iguazu 1 SARI IGR IGU http://www.aa2000.com.ar/iguazu https://en.wikipedia.org/wiki/Cataratas_del_Ig... IguaƧu 750 2018-09-13T12:34:47+00:00

5 rows Ɨ 23 columns

InĀ [22]:
infoairports.columns
Out[22]:
Index(['id', 'ident', 'type', 'name', 'latitude_deg', 'longitude_deg',
       'elevation_ft', 'continent', 'country_name', 'iso_country',
       'region_name', 'iso_region', 'local_region', 'municipality',
       'scheduled_service', 'gps_code', 'iata_code', 'local_code', 'home_link',
       'wikipedia_link', 'keywords', 'score', 'last_updated'],
      dtype='object')
InĀ [23]:
keep=['name','type','latitude_deg', 'longitude_deg','elevation_ft','region_name','municipality']
infoairports=infoairports.loc[:,keep]

infoairports.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 943 entries, 0 to 942
Data columns (total 7 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   name           943 non-null    object
 1   type           943 non-null    object
 2   latitude_deg   943 non-null    object
 3   longitude_deg  943 non-null    object
 4   elevation_ft   908 non-null    object
 5   region_name    943 non-null    object
 6   municipality   927 non-null    object
dtypes: object(7)
memory usage: 51.7+ KB
InĀ [24]:
numericCols=['latitude_deg', 'longitude_deg','elevation_ft']
infoairports[numericCols]=infoairports.loc[:,numericCols].apply(lambda x:pd.to_numeric(x))
infoairports.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 943 entries, 0 to 942
Data columns (total 7 columns):
 #   Column         Non-Null Count  Dtype  
---  ------         --------------  -----  
 0   name           943 non-null    object 
 1   type           943 non-null    object 
 2   latitude_deg   943 non-null    float64
 3   longitude_deg  943 non-null    float64
 4   elevation_ft   908 non-null    float64
 5   region_name    943 non-null    object 
 6   municipality   927 non-null    object 
dtypes: float64(3), object(4)
memory usage: 51.7+ KB
InĀ [25]:
airports=gpd.GeoDataFrame(data=infoairports.copy(),
                 geometry=gpd.points_from_xy(infoairports.longitude_deg,
                                             infoairports.latitude_deg),
                 crs=argentina.crs.to_epsg())

airports_9252=airports.to_crs(9252)

base = argentina_9252.plot(color='white', edgecolor='black')
airports_9252.plot(ax=base)
Out[25]:
<Axes: >
No description has been provided for this image
InĀ [26]:
airports_9252['type'].value_counts()
Out[26]:
type
small_airport     687
heliport          144
medium_airport     68
closed             41
large_airport       2
balloonport         1
Name: count, dtype: int64
InĀ [27]:
airports_9252.rename(columns={'type':'kind'},inplace=True)
airports_9252.to_file(os.path.join("maps","argentinaMaps_9252.gpkg"), layer='airports', driver="GPKG")
InĀ [28]:
#Exercise 4
InĀ [29]:
argentina_9252
Out[29]:
COUNTRY geometry
10 Argentina MULTIPOLYGON (((2319238.057 5961851.998, 23223...
InĀ [30]:
argentina_9252.boundary
Out[30]:
10    MULTILINESTRING ((2319238.057 5961851.998, 232...
dtype: geometry
InĀ [31]:
argentina_9252.boundary.plot()
Out[31]:
<Axes: >
No description has been provided for this image
InĀ [32]:
type(argentina_9252.boundary)
Out[32]:
geopandas.geoseries.GeoSeries
InĀ [33]:
argentina_9252.boundary.to_frame()
Out[33]:
0
10 MULTILINESTRING ((2319238.057 5961851.998, 232...
InĀ [34]:
argentina_border=argentina_9252.boundary.to_frame()

argentina_border['name']='Argentina'

argentina_border.rename(columns={0:'geometry'},inplace=True)

argentina_border = argentina_border.set_geometry("geometry")

argentina_border.crs
Out[34]:
<Projected CRS: EPSG:9252>
Name: MMN / Argentina 2
Axis Info [cartesian]:
- X[north]: Northing (metre)
- Y[east]: Easting (metre)
Area of Use:
- name: Argentina - Tierra del Fuego onshore.
- bounds: (-68.64, -55.11, -63.73, -52.59)
Coordinate Operation:
- name: Argentina zone 2
- method: Transverse Mercator
Datum: Ministerio de Marina Norte
- Ellipsoid: International 1924
- Prime Meridian: Greenwich
InĀ [35]:
#Exercise 5
InĀ [36]:
argentina_states=gpd.read_file("https://github.com/Luis9193/geodf_operations/raw/main/maps/arg_admbnda_adm1_unhcr2017.shp")
argentina_municipalities=gpd.read_file("https://github.com/Luis9193/geodf_operations/raw/main/maps/arg_admbnda_adm2_unhcr2017.shp")
InĀ [37]:
type(argentina_states), type(argentina_municipalities)
Out[37]:
(geopandas.geodataframe.GeoDataFrame, geopandas.geodataframe.GeoDataFrame)
InĀ [38]:
argentina_states.geometry.head()
Out[38]:
0    MULTIPOLYGON Z (((-6918884.037 -4931769.351 0....
1    POLYGON Z ((-7566501.154 -2903626.584 0.000, -...
2    POLYGON Z ((-6929548.312 -2770568.731 0.000, -...
3    MULTIPOLYGON Z (((-7424844.932 -5660565.812 0....
4    POLYGON Z ((-6507173.600 -4100891.637 0.000, -...
Name: geometry, dtype: geometry
InĀ [39]:
argentina_municipalities.geometry.head()
Out[39]:
0    POLYGON Z ((-66.53119 -28.53104 0.00000, -66.5...
1    POLYGON Z ((-60.16947 -38.17843 0.00000, -60.0...
2    POLYGON Z ((-65.26270 -24.31436 0.00000, -65.2...
3    POLYGON Z ((-56.90895 -37.18880 0.00000, -56.9...
4    POLYGON Z ((-61.98441 -34.51765 0.00000, -61.8...
Name: geometry, dtype: geometry
InĀ [40]:
argentina_states.crs
Out[40]:
<Projected CRS: EPSG:3857>
Name: WGS 84 / Pseudo-Mercator
Axis Info [cartesian]:
- X[east]: Easting (metre)
- Y[north]: Northing (metre)
Area of Use:
- name: World between 85.06Ā°S and 85.06Ā°N.
- bounds: (-180.0, -85.06, 180.0, 85.06)
Coordinate Operation:
- name: Popular Visualisation Pseudo-Mercator
- method: Popular Visualisation Pseudo Mercator
Datum: World Geodetic System 1984 ensemble
- Ellipsoid: WGS 84
- Prime Meridian: Greenwich
InĀ [41]:
argentina_municipalities.crs
Out[41]:
<Geographic 2D CRS: EPSG:4326>
Name: WGS 84
Axis Info [ellipsoidal]:
- Lat[north]: Geodetic latitude (degree)
- Lon[east]: Geodetic longitude (degree)
Area of Use:
- name: World.
- bounds: (-180.0, -90.0, 180.0, 90.0)
Datum: World Geodetic System 1984 ensemble
- Ellipsoid: WGS 84
- Prime Meridian: Greenwich
InĀ [42]:
argentina_states=argentina_states.to_crs(9252)
argentina_municipalities=argentina_municipalities.to_crs(9252)
InĀ [43]:
#Exercise 6
InĀ [44]:
argentina_municipalities.plot(facecolor='lightgrey', edgecolor='black',linewidth=0.2)
Out[44]:
<Axes: >
No description has been provided for this image
InĀ [45]:
argentina_municipalities.head()
Out[45]:
ADM0_ES ADM0_PCODE ADM1_ES ADM1_PCODE ADM2_ES ADM2_REF ADM2_PCODE geometry
0 Argentina AR La Rioja AR046 Arauco Arauco AR046007 POLYGON Z ((2741643.797 6842320.077 0.000, 274...
1 Argentina AR Buenos Aires AR006 Tres Arroyos Tres Arroyos AR006833 POLYGON Z ((3274415.472 5737734.786 0.000, 328...
2 Argentina AR Jujuy AR038 El Carmen El Carmen AR038014 POLYGON Z ((2879495.127 7306897.453 0.000, 287...
3 Argentina AR Buenos Aires AR006 Pinamar Pinamar AR006644 POLYGON Z ((3575679.580 5815434.698 0.000, 357...
4 Argentina AR Buenos Aires AR006 General Pinto General Pinto AR006351 POLYGON Z ((3144724.317 6158577.347 0.000, 315...
InĀ [46]:
argentina_municipalities.ADM1_ES.value_counts()
Out[46]:
ADM1_ES
Buenos Aires              135
Santiago del Estero        27
CĆ³rdoba                    26
Corrientes                 25
Chaco                      25
Salta                      23
La Pampa                   22
Santa Fe                   19
San Juan                   19
La Rioja                   18
Mendoza                    18
Entre RĆ­os                 17
Misiones                   17
TucumƔn                    17
Catamarca                  16
NeuquƩn                    16
Jujuy                      16
Chubut                     15
Ciudad de Buenos Aires     15
RĆ­o negro                  13
San Luis                    9
Formosa                     9
Santa Cruz                  7
Tierra del Fuego            2
Name: count, dtype: int64
InĀ [47]:
argentina_municipalities[argentina_municipalities.ADM1_ES=='Buenos Aires'].plot()
Out[47]:
<Axes: >
No description has been provided for this image
InĀ [48]:
argentina_municipalities[argentina_municipalities.ADM1_ES=='Buenos Aires'].unary_union
Out[48]:
No description has been provided for this image
InĀ [49]:
BuenosAires_union=argentina_municipalities[argentina_municipalities.ADM1_ES=='Buenos Aires'].unary_union
InĀ [50]:
type(BuenosAires_union)
Out[50]:
shapely.geometry.multipolygon.MultiPolygon
InĀ [51]:
gpd.GeoDataFrame(index=[0],data={'ADM':'Buenos Aires'},
                 crs=argentina_municipalities.crs,
                 geometry=[BuenosAires_union])
Out[51]:
ADM geometry
0 Buenos Aires MULTIPOLYGON Z (((3079143.360 5498808.279 0.00...
InĀ [52]:
#Con dissolve
argentina_municipalities[argentina_municipalities.ADM1_ES=='Buenos Aires'].dissolve().plot()
Out[52]:
<Axes: >
No description has been provided for this image
InĀ [53]:
BuenosAires_dissolve=argentina_municipalities[argentina_municipalities.ADM1_ES=='Buenos Aires'].dissolve()
type(BuenosAires_dissolve)
Out[53]:
geopandas.geodataframe.GeoDataFrame
InĀ [54]:
#Exercise 7
InĀ [55]:
airports_9252
Out[55]:
name kind latitude_deg longitude_deg elevation_ft region_name municipality geometry
0 Minister Pistarini International Airport large_airport -34.822200 -58.535800 67.0 Buenos Aires Province Buenos Aires (Ezeiza) POINT (3459143.742 6096878.264)
1 Jorge Newbery Airpark large_airport -34.559200 -58.415600 18.0 Buenos Aires (Autonomous City) Buenos Aires POINT (3473326.500 6125055.331)
2 Malvinas Argentinas Airport medium_airport -54.843300 -68.295800 102.0 Tierra del Fuego Province Ushuaia POINT (2545204.629 3922073.788)
3 El Calafate - Commander Armando Tola Internati... medium_airport -50.280300 -72.053101 669.0 Santa Cruz Province El Calafate POINT (2282364.042 4425601.501)
4 Cataratas Del IguazĆŗ International Airport medium_airport -25.737301 -54.473400 916.0 Misiones Province Puerto Iguazu POINT (3967392.078 7072420.841)
... ... ... ... ... ... ... ... ...
938 Agrodistribuidora Airstrip closed -29.220089 -61.760298 220.0 Santa Fe Province Tostado POINT (3204887.574 6746621.896)
939 Dayry Partners Americas Manufacturing Argentin... heliport -32.440000 -63.228900 639.0 CĆ³rdoba Province Villa Nueva POINT (3043070.390 6396750.732)
940 Villa UniĆ³n Airport closed -29.422180 -62.789526 248.0 Santiago del Estero Province Villa UniĆ³n POINT (3103251.602 6729935.094)
941 Roca Heliport heliport -32.060000 -64.779400 3444.0 CĆ³rdoba Province Yacanto de Calamuchita POINT (2898684.357 6445788.634)
942 Austral S.A. Heliport heliport -52.738600 -68.572500 290.0 Tierra del Fuego Province Yacimiento CaƱadĆ³n Alfa POINT (2528839.013 4156471.091)

943 rows Ɨ 8 columns

InĀ [56]:
airports_9252.kind.value_counts()
Out[56]:
kind
small_airport     687
heliport          144
medium_airport     68
closed             41
large_airport       2
balloonport         1
Name: count, dtype: int64
InĀ [57]:
medium_airport=airports_9252[airports_9252.kind=='medium_airport']
medium_airport.unary_union
Out[57]:
No description has been provided for this image
InĀ [58]:
medium_airport.unary_union.convex_hull
Out[58]:
No description has been provided for this image
InĀ [59]:
MediumAirport_hull= gpd.GeoDataFrame(index=[0],
                                    crs=medium_airport.crs,
                                    geometry=[medium_airport.unary_union.convex_hull])
MediumAirport_hull['name']='medium airports hull'

MediumAirport_hull
Out[59]:
geometry name
0 POLYGON ((2545204.629 3922073.788, 2282364.042... medium airports hull
InĀ [60]:
base=argentina_9252.plot(facecolor='yellow')
medium_airport.plot(ax=base)
MediumAirport_hull.plot(ax=base,facecolor='green',
                       edgecolor='white',alpha=0.4,
                       hatch='X')
Out[60]:
<Axes: >
No description has been provided for this image
InĀ [61]:
#Exercise 8
InĀ [62]:
centroidX,centroidY=argentina_9252.centroid.x.values[0],argentina_9252.centroid.y.values[0]

MunisN_argentina=argentina_municipalities.cx[:,centroidY:]
MunisS_argentina=argentina_municipalities.cx[:,:centroidY]
MunisW_argentina=argentina_municipalities.cx[:centroidX,:]
MunisE_argentina=argentina_municipalities.cx[centroidX:,:]
InĀ [63]:
base=MunisN_argentina.plot(facecolor='yellow', edgecolor='black',linewidth=0.2, alpha=0.6)
MunisS_argentina.plot(facecolor='grey', edgecolor='black',linewidth=0.2,ax=base, alpha=0.4)
Out[63]:
<Axes: >
No description has been provided for this image
InĀ [64]:
munisNS_argentina=MunisN_argentina.overlay(MunisS_argentina, how="intersection",keep_geom_type=True)
munisNS_argentina.plot()
Out[64]:
<Axes: >
No description has been provided for this image
InĀ [65]:
MunisN_argentina.overlay(MunisS_argentina, how="symmetric_difference",keep_geom_type=False).plot()
Out[65]:
<Axes: >
No description has been provided for this image